Although computers were once isolated and had minimal or little interaction with other computers, today's computers interact with a wide variety of other computers through communications networks, such as Local Area Networks (LANs) and Wide Area Networks (WANs). With the wide-spread growth of the INTERNE™, connectivity between computers is becoming more important and has opened up many new applications and technologies. The growth of large-scale networks, and the wide-spread availability of low-cost personal computers, has fundamentally changed the way that many people work, interact, communicate, and play.
One increasing popular form of networking may generally be referred to as virtual computing systems, which can use protocols such as Remote Desktop Protocol (RDP), Independent Computing Architecture (ICA), and others to share a desktop and other applications with a remote client over a remote session. Such computing systems typically transmit the keyboard presses and mouse clicks or selections from the client to a server, relaying the screen updates back in the other direction over a network connection (e.g., the INTERNET). As such, the user has the experience as if their machine is operating as part of a LAN, when in reality the client device is only sent screenshots of the applications as they appear on the server side.
Compression algorithms are important to reducing the bandwidth used by a remote session to levels that make transmission over LANs, wireless LANs (wLANs) and WANs. These compression algorithms trade processing time on a server in exchange for a lower bandwidth required for the session.
Too high an amount of processing time can inhibit scalability of the server as well as increase the time required to encode a frame, which reduces the overall framerate (FPS) of the remote session. A low FPS negatively impacts the user experience because the session may appeal jerky and feel unresponsive.
Present encoding systems are lacking in ways to take advantage of the multiple processors or processing cores found in many contemporary computers. This lack of maximization of processing resources causes compression time to be higher than it could be.